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active | true |
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title | Data Access |
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| Data AccessData Type | Download all |
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Images (TIFF, 11 GB) | | Abbreviations (TXT) | | Annotations (DAT) | |
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Localtab |
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title | Detailed Description |
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| Detailed DescriptionImage Statistics |
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Modalities | Pathology | Number of Patients | 200 | Number of Images | 18,365 | Images Size (GB) | 11 |
- All single-cell images in this dataset were produced using the M8 digital microscope/scanner (Precipoint GmbH, Freising/Germany) from peripheral blood smears at 100x magnification and oil immersion. A coverage of 14.14 Pixels per Micron is given by the manufacturer.
- The abbreviations used for morphological classes in annotations and the folder structure are defined in abbreviations.txt
- Annotations are given in the file annotations.dat. In this file, the first column gives the name of the respective image file and the second column the morphological class assigned during the gold-standard annotation. If a single-cell image was re-annotated, the result of the first re-annotation process by a second independent annotator is given in the third column, and the result of the second re-annotation process after a time interval of 11 months by the same re-annotator in the fourth column. If a single-cell image was not re-annotated, the third and fourth column contain the value "nan".
- For details of the scanning and annotation process, please refer to:
- Matek et al., Human-level recognition of blast cells in acute myeloid leukemia with convolutional neural networks., Nat. Mach. Intell. (2019)
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title | Citations & Data Usage Policy |
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| Citations & Data Usage PolicyThese collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work: Info |
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| "Matek, C., Schwarz, S., Marr, C., & Spiekermann, K. (2019). A Single-cell Morphological Dataset of Leukocytes from AML Patients and Non-malignant Controls [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/tcia.2019.36f5o9ld" |
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title | Publication Citation |
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| 1) Matek Matek, C., Schwarz, S., Spiekermann, K. et al., Human-level recognition of blast cells in acute myeloid leukemia leukaemia with convolutional neural networks, Nature Machine Intelligence . Nat Mach Intell 1, 538–544 (2019, accepted)). https://doi.org/10.1038/s42256-019-0101-9 |
Info |
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| Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7 |
Other Publications Using This DataTCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
Localtab |
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| Version 1 (Current): Updated 2019/10/24Data Type | Download all |
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Images (TIFF, 11 GB) | | Abbreviations (TXT)
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